1 |
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2 | #include <TROOT.h>
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3 | #include <TCanvas.h>
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4 | #include <TProfile.h>
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5 | #include <TTimer.h>
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6 | #include <TH1F.h>
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7 | #include <TH2F.h>
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8 | #include <Getline.h>
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9 | #include <TLine.h>
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10 | #include <TMath.h>
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11 |
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12 | #include <stdint.h>
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13 | #include <cstdio>
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14 |
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15 | #define HAVE_ZLIB
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16 | #include "fits.h"
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17 | //#include "TPKplotevent.c"
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18 | //#include "FOpenDataFile.c"
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19 | #include "FOpenCalibFile.c"
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20 |
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21 | #include "Region.h"
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22 | #include "zerosearch.h"
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23 | #include "zerosearch.C"
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24 |
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25 | #define NPIX 1440
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26 | #define NCELL 1024
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27 |
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28 | // data access and treatment
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29 | #define FAD_MAX_SAMPLES 1024
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30 |
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31 | vector<int16_t> data;
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32 | vector<int16_t> data_offset;
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33 |
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34 | unsigned int data_num;
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35 |
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36 | size_t data_n;
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37 | UInt_t data_px;
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38 | UInt_t data_roi;
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39 | int NEvents;
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40 |
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41 | size_t drs_n;
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42 | vector<float> drs_basemean;
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43 | vector<float> drs_gainmean;
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44 | vector<float> drs_triggeroffsetmean;
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45 |
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46 | int FOpenDataFile( fits & );
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47 |
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48 |
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49 | vector<float> Ameas(FAD_MAX_SAMPLES); // copy of the data (measured amplitude
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50 | vector<float> N1mean(FAD_MAX_SAMPLES); // mean of the +1 -1 ch neighbors
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51 | vector<float> N2mean(FAD_MAX_SAMPLES); // mean of the +2 -2 ch neighbors
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52 | vector<float> Vcorr(FAD_MAX_SAMPLES); // corrected Values
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53 | vector<float> Vdiff(FAD_MAX_SAMPLES); // numerical derivative
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54 |
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55 | vector<float> Vslide(FAD_MAX_SAMPLES); // sliding average result
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56 | vector<float> Vcfd(FAD_MAX_SAMPLES); // CDF result
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57 | vector<float> Vcfd2(FAD_MAX_SAMPLES); // CDF result + 2nd sliding average
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58 |
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59 | #include "factfir.C"
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60 |
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61 | float getValue( int, int );
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62 | void computeN1mean( int );
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63 | void removeSpikes( int );
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64 |
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65 | // histograms
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66 | const int Ntypes = 7;
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67 | const unsigned int // arranged by Dominik
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68 | tAmeas = 0,
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69 | tN1mean = 1,
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70 | tVcorr = 2,
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71 | tVtest = 3,
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72 | tVslide = 4,
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73 | tVcfd = 5,
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74 | tVcfd2 = 6;
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75 |
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76 | TH1F* h;
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77 | TH2F* hStartCell; // id of the DRS physical pipeline cell where readout starts
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78 | // x = pixel id, y = DRS cell id
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79 | TH2F hPixelCellData("PixelPedestal", "PixelPedestal", NCELL, 0., NCELL, 200, -50., 150.);
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80 |
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81 | void BookHistos( int );
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82 |
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83 | // Create a canvas
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84 | TCanvas* CW;
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85 | TCanvas* cFilter;
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86 |
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87 | int spikeDebug = 1;
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88 |
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89 |
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90 | int fana(
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91 | char *datafilename = "../raw/20110916_025.fits",
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92 | const char *drsfilename = "../raw/20110916_024.drs.fits",
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93 | int pixelnr = 0,
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94 | int firstevent = 0,
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95 | int nevents = -1 ){
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96 | // read and analyze FACT raw data
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97 |
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98 | // sliding window filter settings
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99 | int k_slide = 16;
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100 | vector<double> a_slide(k_slide, 1);
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101 | double b_slide = k_slide;
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102 |
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103 | // CFD filter settings
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104 | int k_cfd = 10;
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105 | vector<double> a_cfd(k_cfd, 0);
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106 | double b_cfd = 1.;
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107 | a_cfd[0]=0.75;
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108 | a_cfd[k_cfd-1]=-1.;
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109 |
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110 | // 2nd slinding window filter
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111 | //int ks2 = 16;
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112 | //vector<double> as2(ks2, 1);
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113 | //double bs2 = ks2;
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114 | gROOT->SetStyle("Plain");
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115 |
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116 | //-------------------------------------------
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117 | // Open the file
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118 | //-------------------------------------------
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119 | fits datafile( datafilename );
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120 | if (!datafile) {
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121 | printf( "Could not open the file: %s\n", datafilename );
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122 | return 1;
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123 | }
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124 |
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125 | // access data
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126 | NEvents = FOpenDataFile( datafile );
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127 |
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128 | printf("number of events in file: %d\n", NEvents);
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129 |
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130 | // compare the number of events in the data file with the nevents the
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131 | // the user would like to read. nevents = -1 means: read all
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132 | if ( nevents == -1 || nevents > NEvents ) nevents = NEvents;
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133 |
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134 |
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135 | //-------------------------------------------
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136 | //Get the DRS calibration
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137 | //-------------------------------------------
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138 |
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139 | FOpenCalibFile(drsfilename, drs_basemean, drs_gainmean, drs_triggeroffsetmean, drs_n);
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140 |
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141 | //-------------------------------------------
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142 | //Check the sizes of the data columns
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143 | //-------------------------------------------
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144 | if(drs_n!=data_n)
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145 | {
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146 | cout << "Data and DRS file incompatible (Px*ROI disagree)" << endl;
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147 | return 1;
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148 | }
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149 | // Book the histograms
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150 | BookHistos( data_roi );
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151 |
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152 | // Loop over events
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153 | cout << "--------------------- Data --------------------" << endl;
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154 |
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155 | float value;
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156 | TH1F * sp = new TH1F("spektrum", "test of Stepktrum", 256, -0.5, 63.5);
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157 |
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158 | for ( int ev = firstevent; ev < firstevent + nevents; ev++) {
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159 |
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160 | datafile.GetRow( ev );
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161 |
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162 | if (ev % 50 ==0){
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163 | cout << "Event number: " << data_num << endl;
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164 | }
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165 |
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166 | for ( int pix = 0; pix < 1440; pix++ ){
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167 | hStartCell->Fill( pix, data_offset[pix] );
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168 | }
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169 |
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170 | for ( unsigned int sl = 0; sl < data_roi; sl++){
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171 | value = getValue(sl, pixelnr);
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172 | //printf("value = %f\n", value);
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173 | Ameas[ sl ] = value;
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174 | h[tAmeas].SetBinContent(sl, value);
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175 |
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176 | }
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177 |
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178 | computeN1mean( data_roi );
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179 | removeSpikes( data_roi );
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180 |
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181 | for ( unsigned int sl = 0; sl < data_roi; sl++){
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182 | hPixelCellData.Fill(sl, Vcorr[ sl ]);
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183 | }
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184 |
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185 | // filter Vcorr with sliding average using FIR filter function
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186 | factfir(b_slide , a_slide, k_slide, Vcorr, Vslide);
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187 |
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188 | // filter Vslide with CFD using FIR filter function
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189 | factfir(b_cfd , a_cfd, k_cfd, Vslide, Vcfd);
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190 | // filter Vcfd with sliding average using FIR filter function
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191 | factfir(b_slide , a_slide, k_slide, Vcfd, Vcfd2);
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192 |
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193 | if ( spikeDebug ){
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194 | for ( unsigned int sl = 0; sl < data_roi; sl++){
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195 | h[tVslide].SetBinContent( sl, Vslide[sl] );
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196 | h[tVcfd].SetBinContent( sl, Vcfd[sl] );
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197 | h[tVcfd2].SetBinContent( sl, Vcfd2[sl] );
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198 | }
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199 | }
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200 |
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201 | vector<Region> * zeros = zerosearch( Vcfd2, -1, 1, 0);
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202 | ShiftRegionBy(*zeros, -k_slide/2);
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203 | EnlargeRegion(*zeros, 10, 20);
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204 | findAbsMaxInRegions( *zeros, Vslide);
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205 | if (zeros->size() == 0 ){
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206 | continue;
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207 | }
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208 | // check value of Vside at zero position
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209 | for (unsigned int i=0; i<zeros->size(); i++){
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210 | cout << zeros->at(i).maxPos << ":\t" << zeros->at(i).maxVal <<endl;
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211 | sp->Fill( zeros->at(i).maxVal );
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212 | }
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213 |
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214 | if ( spikeDebug ){
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215 |
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216 | CW->cd( tAmeas + 1);
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217 | gPad->SetGrid();
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218 | h[tAmeas].Draw();
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219 |
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220 | CW->cd( tN1mean + 1);
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221 | gPad->SetGrid();
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222 | h[tN1mean].Draw();
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223 |
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224 | CW->cd( tVcorr + 1);
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225 | gPad->SetGrid();
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226 | h[tVcorr].Draw();
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227 |
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228 | // CW->cd( tVtest + 1);
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229 | // gPad->SetGrid();
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230 | // h[tVtest].Draw();
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231 |
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232 | cFilter->cd( Ntypes - tVslide );
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233 | cFilter->cd(1);
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234 | gPad->SetGrid();
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235 | h[tVslide].Draw();
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236 |
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237 | cFilter->cd( Ntypes - tVcfd );
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238 | cFilter->cd(2);
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239 | gPad->SetGrid();
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240 | h[tVcfd].Draw();
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241 |
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242 | TLine zeroline(0, 0, 1024, 0);
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243 | zeroline.SetLineColor(kBlue);
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244 | zeroline.Draw();
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245 |
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246 | cFilter->cd( Ntypes - tVcfd2 );
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247 | cFilter->cd(3);
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248 | gPad->SetGrid();
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249 | h[tVcfd2].Draw();
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250 |
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251 | zeroline.Draw();
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252 |
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253 | CW->Update();
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254 | cFilter->Update();
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255 |
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256 | //Process gui events asynchronously during input
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257 | TTimer timer("gSystem->ProcessEvents();", 50, kFALSE);
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258 | timer.TurnOn();
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259 | TString input = Getline("Type 'q' to exit, <return> to go on: ");
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260 | timer.TurnOff();
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261 | if (input=="q\n") break;
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262 | }
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263 |
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264 |
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265 | }
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266 |
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267 | TCanvas * cSpektrum = new TCanvas();
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268 | cSpektrum->cd();
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269 | sp->Draw();
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270 | TCanvas * cStartCell = new TCanvas();
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271 | cStartCell->cd();
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272 | hStartCell->Draw();
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273 | hPixelCellData.Draw();
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274 |
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275 | delete cStartCell;
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276 |
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277 | return( 0 );
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278 | }
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279 |
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280 | void removeSpikes(int Samples){
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281 |
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282 | const float fract = 0.8;
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283 | float x, xp, xpp, x3p;
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284 |
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285 | // assume that there are no spikes
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286 | for ( int i = 0; i < Samples; i++) Vcorr[i] = Ameas[i];
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287 |
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288 | // find the spike and replace it by mean value of neighbors
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289 | for ( int i = 0; i < Samples; i++) {
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290 |
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291 | // printf("Vcorr[%d] = %f, Ameas[%d] = %f\n", i, Vcorr[ i ], i, Ameas[ i ] );
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292 |
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293 | x = Ameas[i] - N1mean[i];
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294 |
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295 | if ( x < -5. ){ // a spike candidate
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296 | // check consistency with a single channel spike
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297 | xp = Ameas[i+1] - N1mean[i+1];
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298 | xpp = Ameas[i+2] - N1mean[i+2];
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299 | x3p = Ameas[i+3] - N1mean[i+3];
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300 |
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301 | // printf("candidates x[%d] = %f; xp = %f; xpp = %f, x3p = %f\n", i, x, xp, xpp, x3p);
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302 |
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303 | if ( Ameas[i+2] - ( Ameas[i] + Ameas[i+3] )/2. > 10. ){
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304 | // printf("double spike candidate\n");
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305 | Vcorr[i+1] = ( Ameas[i] + Ameas[i+3] )/2.;
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306 | Vcorr[i+2] = ( Ameas[i] + Ameas[i+3] )/2.;
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307 | // printf("Vcorr[%d] = %f %f %f %f\n", i, Vcorr[i], Vcorr[i+1], Vcorr[i+2], Vcorr[ i+3 ]);
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308 | // printf("Ameas[%d] = %f %f %f %f\n", i, Ameas[ i ], Ameas[ i+1 ], Ameas[ i+2 ], Ameas[i+3]);
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309 | i = i + 3;
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310 | }
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311 | else{
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312 |
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313 | if ( ( xp > -2.*x*fract ) && ( xpp < -10. ) ){
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314 | Vcorr[i+1] = N1mean[i+1];
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315 | // printf("Vcorr[%d] = %f %f %f\n", i, Vcorr[i], Vcorr[i+1], Vcorr[i+2]);
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316 | // N1mean[i+1] = (Ameas[i] - Ameas[i+2] / 2.);
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317 | N1mean[i+2] = (Ameas[i+1] - Ameas[i+3] / 2.);
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318 | i = i + 2;//do not care about the next sample it was the spike
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319 | }
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320 | // treatment for the end of the pipeline must be added !!!
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321 | }
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322 | }
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323 | else{
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324 | // do nothing
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325 | }
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326 | } // end of spike search and correction
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327 | for ( int i = 0; i < Samples; i++ ) h[ tVcorr ].SetBinContent( i, Vcorr[i] );
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328 | }
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329 |
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330 | void computeN1mean( int Samples ){
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331 |
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332 | // compute the mean of the left and right neighbors of a channel
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333 |
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334 | for( int i = 0; i < Samples; i++){
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335 | if (i == 0){ // use right sample es mean
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336 | N1mean[i] = Ameas[i+1];
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337 | }
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338 | else if ( i == Samples-1 ){ //use left sample as mean
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339 | N1mean[i] = Ameas[i-1];
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340 | }
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341 | else{
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342 | N1mean[i] = ( Ameas[i-1] + Ameas[i+1] ) / 2.;
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343 | }
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344 | h[tN1mean].SetBinContent(i, Ameas[i] - N1mean[i]);
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345 | }
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346 | } // end of computeN1mean computation
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347 |
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348 | float getValue( int slice, int pixel ){
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349 |
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350 | const float dconv = 2000/4096.0;
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351 |
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352 | float vraw, vcal;
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353 |
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354 | unsigned int pixel_pt;
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355 | unsigned int slice_pt;
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356 | unsigned int cal_pt;
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357 | unsigned int drs_cal_offset;
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358 |
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359 | // printf("pixel = %d, slice = %d\n", slice, pixel);
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360 |
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361 | pixel_pt = pixel * data_roi;
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362 | slice_pt = pixel_pt + slice;
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363 | drs_cal_offset = ( slice + data_offset[ pixel ] )%data_roi;
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364 | cal_pt = pixel_pt + drs_cal_offset;
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365 |
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366 | vraw = data[ slice_pt ] * dconv;
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367 | vcal = ( vraw - drs_basemean[ cal_pt ] - drs_triggeroffsetmean[ slice_pt ] ) / drs_gainmean[ cal_pt ]*1907.35;
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368 |
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369 | return( vcal );
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370 | }
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371 |
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372 | void BookHistos( int Samples ){
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373 | // booking and parameter settings for all histos
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374 |
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375 | h = new TH1F[ Ntypes ];
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376 |
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377 | for ( int type = 0; type < Ntypes; type++){
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378 |
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379 | h[ type ].SetBins(Samples, 0, Samples);
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380 | h[ type ].SetLineColor(1);
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381 | h[ type ].SetLineWidth(2);
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382 |
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383 | // set X axis paras
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384 | h[ type ].GetXaxis()->SetLabelSize(0.1);
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385 | h[ type ].GetXaxis()->SetTitleSize(0.1);
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386 | h[ type ].GetXaxis()->SetTitleOffset(1.2);
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387 | h[ type ].GetXaxis()->SetTitle(Form("Time slice (%.1f ns/slice)", 1./2.));
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388 |
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389 | // set Y axis paras
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390 | h[ type ].GetYaxis()->SetLabelSize(0.1);
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391 | h[ type ].GetYaxis()->SetTitleSize(0.1);
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392 | h[ type ].GetYaxis()->SetTitleOffset(0.3);
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393 | h[ type ].GetYaxis()->SetTitle("Amplitude (a.u.)");
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394 | }
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395 | CW = new TCanvas("CW","DRS Waveform",10,10,800,600);
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396 | CW->Divide(1, 3);
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397 | cFilter = new TCanvas("cFilter","filtered DRS Waveforms",10,10,800,600);
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398 | cFilter->Divide(1, 3);
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399 |
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400 | hStartCell = new TH2F("StartCell", "StartCell", 1440, 0., 1440., 1024, 0., 1024);
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401 |
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402 | }
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403 | int FOpenDataFile(fits &datafile){
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404 |
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405 | /* cout << "-------------------- Data Header -------------------" << endl;
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406 | datafile.PrintKeys();
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407 | cout << "------------------- Data Columns -------------------" << endl;
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408 | datafile.PrintColumns();
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409 | */
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410 |
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411 | //Get the size of the data column
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412 | data_roi = datafile.GetUInt("NROI"); // Value from header
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413 | data_px = datafile.GetUInt("NPIX");
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414 | data_n = datafile.GetN("Data"); //Size of column "Data" = #Pixel x ROI
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415 |
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416 | //Set the sizes of the data vectors
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417 | data.resize(data_n,0);
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418 | data_offset.resize(data_px,0);
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419 |
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420 | //Link the data to variables
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421 | datafile.SetRefAddress("EventNum", data_num);
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422 | datafile.SetVecAddress("Data", data);
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423 | datafile.SetVecAddress("StartCellData", data_offset);
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424 | datafile.GetRow(0);
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425 |
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426 | cout << "Opening data file successful..." << endl;
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427 |
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428 | return datafile.GetNumRows() ;
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429 | }
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430 |
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